Update README.md

Updating installing instructions, bringing it into parity with the docs. Including reference to CUDA version with Conda. Pointing readers to the docs for building and installing from source.

README.md

@@ -255,24 +255,28 @@ pairwise_distance(in1, in2, out=output, metric="euclidean")
 
 ## Installing
 
-RAFT itself can be installed through conda, [CMake Package Manager (CPM)](https://github.com/cpm-cmake/CPM.cmake), pip, or by building the repository from source. Please refer to the [build instructions](docs/source/build.md) for more a comprehensive guide on installing and building RAFT and using it in downstream projects.
-
 ### Conda
 
 The easiest way to install RAFT is through conda and several packages are provided.
 - `libraft-headers` RAFT headers
-- `libraft` (optional) shared library of pre-compiled template instantiations and runtime APIs.
+- `libraft` (optional) shared library containing pre-compiled template instantiations and runtime API.
 - `pylibraft` (optional) Python wrappers around RAFT algorithms and primitives.
 - `raft-dask` (optional) enables deployment of multi-node multi-GPU algorithms that use RAFT `raft::comms` in Dask clusters.
 
-Use the following command to install all of the RAFT packages with conda (replace `rapidsai` with `rapidsai-nightly` to install more up-to-date but less stable nightly packages). `mamba` is preferred over the `conda` command.
+Use the following command, depending on your CUDA version, to install all of the RAFT packages with conda (replace `rapidsai` with `rapidsai-nightly` to install more up-to-date but less stable nightly packages). `mamba` is preferred over the `conda` command.
+```bash
+# for CUDA 11.8
+mamba install -c rapidsai -c conda-forge -c nvidia raft-dask pylibraft cuda-version=11.8
+```
+
 ```bash
-mamba install -c rapidsai -c conda-forge -c nvidia raft-dask pylibraft
+# for CUDA 12.0
+mamba install -c rapidsai -c conda-forge -c nvidia raft-dask pylibraft cuda-version=12.0
 ```
 
 You can also install the conda packages individually using the `mamba` command above.
 
-After installing RAFT, `find_package(raft COMPONENTS compiled distributed)` can be used in your CUDA/C++ cmake build to compile and/or link against needed dependencies in your raft target. `COMPONENTS` are optional and will depend on the packages installed.
+After installing RAFT, `find_package(raft COMPONENTS nn distance)` can be used in your CUDA/C++ cmake build to compile and/or link against needed dependencies in your raft target. `COMPONENTS` are optional and will depend on the packages installed.
 
 ### Pip
 
@@ -282,37 +286,9 @@ pip install pylibraft-cu11 --extra-index-url=https://pypi.nvidia.com
 pip install raft-dask-cu11 --extra-index-url=https://pypi.nvidia.com
 ```
 
-### CMake & CPM
-
-RAFT uses the [RAPIDS-CMake](https://github.com/rapidsai/rapids-cmake) library, which makes it easy to include in downstream cmake projects. RAPIDS-CMake provides a convenience layer around CPM. Please refer to [these instructions](https://github.com/rapidsai/rapids-cmake#installation) to install and use rapids-cmake in your project.
-
-#### Example Template Project
-
-You can find an [example RAFT](cpp/template/README.md) project template in the `cpp/template` directory, which demonstrates how to build a new application with RAFT or incorporate RAFT into an existing cmake project.
-
-#### CMake Targets
-
-Additional CMake targets can be made available by adding components in the table below to the `RAFT_COMPONENTS` list above, separated by spaces. The `raft::raft` target will always be available. RAFT headers require, at a minimum, the CUDA toolkit libraries and RMM dependencies.
-
-| Component   | Target              | Description                                              | Base Dependencies                      |
-|-------------|---------------------|----------------------------------------------------------|----------------------------------------|
-| n/a         | `raft::raft`        | Full RAFT header library                                 | CUDA toolkit, RMM, NVTX, CCCL, CUTLASS |
-| compiled    | `raft::compiled`    | Pre-compiled template instantiations and runtime library | raft::raft                             |
-| distributed | `raft::distributed` | Dependencies for `raft::comms` APIs                      | raft::raft, UCX, NCCL                  |
-
-### Source
-
-The easiest way to build RAFT from source is to use the `build.sh` script at the root of the repository:
-1. Create an environment with the needed dependencies:
-```
-mamba env create --name raft_dev_env -f conda/environments/all_cuda-118_arch-x86_64.yaml
-mamba activate raft_dev_env
-```
-```
-./build.sh raft-dask pylibraft libraft tests bench --compile-lib
-```
+## Building and installing RAFT
 
-The [build](docs/source/build.md) instructions contain more details on building RAFT from source and including it in downstream projects. You can also find a more comprehensive version of the above CPM code snippet the [Building RAFT C++ from source](docs/source/build.md#building-raft-c-from-source-in-cmake) section of the build instructions.
+RAFT can be installed through [CMake Package Manager (CPM)](https://github.com/cpm-cmake/CPM.cmake). Please refer to the [build instructions](docs/source/build.md) for more a comprehensive guide on installing and building RAFT and using it in downstream projects.
 
 ## Folder Structure and Contents